Monage 2017 – Chatbot Challenges and New Life for UC
Last week, I attended and spoke at the second iteration of Jeff Pulver’s Monage conference in San Jose – Messaging on the Net. I did the same at the first one last fall, and for more context about Jeff and his event, here’s my UCStrategies writeup about it. At that event, I talked about how “messaging is the new voice,” and I’d say that view was largely validated in San Jose.
There was no shortage of data points showing how messaging is exploding, and while most of the action is in the consumer world, there are lots of lessons learned there for enterprises, and the UC community as well. As a standalone application, there’s not much mystery about messaging’s appeal. Where things get more interesting is when it becomes a vehicle for chatbots – automation – driven by AI.
As analysts and consultants, we touch on this in various ways, but it’s not often we immerse ourselves in the world of chatbots and AI for three days, and that’s what makes Monage a cool event. There is lots to share, and I’ll just cite some takeaways below that speak to the UCC space. Beyond that, I posted some photos to my blog, and the Twitter feed – #Monage – was pretty active.
Selling Chatbots to Enterprises is a Challenge
There were a lot of developers in the house, and they go where the money is. The use cases for chatbots and AI in the consumer world are clear, and we sure saw some great examples, especially around deep engagement with consumers to sell products and brand experiences. Of course, the contact center is the bridge between that opportunity and what might work inside the enterprise, and I gave a presentation along with long-time colleague, Chris Fine, about what’s needed to cross that bridge. Here’s a slide from our talk that provides a sense for what we were getting at.
Inside the enterprise, productivity is really the core application for UC, and this is where chatbots and AI can add value, especially around streamlining processes and automating simple tasks like scheduling meetings. Fair enough, but chatbots and AI are still emerging concepts, without much track record and a bit obtuse for decision-makers. In the bigger scheme of things, we used this slide to illustrate the pyramid of enterprise buying priorities, and as you can see, productivity is pretty far down the list.
To really get their attention, you need to frame those productivity gains in terms of risk reduction, cost savings or revenue growth. We certainly heard some enterprise success stories at Monage, but our message was to show how this is a very different value proposition than selling to brand managers running consumer brands.
Bots are Good for the Seller, but What About for the Buyer?
This question kept popping up in my mind, as we heard many speakers talk about all the cool capabilities their chatbots have. For now, the consumer market is all about driving sales, either online or in-store. Messaging has now become bigger than social media, and with better ad-blocking tools, anyone trying to sell digitally to consumers is coming to realize the value of chatbots. AI has a long way to go still to make the chatbot experience feel personal, but it’s improving as all emerging technologies do. Tech guru Robert Scoble gave us some incredible peeks into the near future, including a demo of an eye-controlled lens interface. Amazing stuff where you interact in real time with a computer just by moving your eyes – no hands, no voice, no body language.
For now, however, chatbots are only as useful as the tools we provide through AI, and the experience just isn’t very good for the buyer. One speaker referred to them as “crapbots”, and until they truly improve, they’re not going to displace many jobs for a while. For now, buyers are pretty much on their own, never really sure if they’re interacting with a chatbot or a real person, and they get nothing good out of it unless a basic level of trust is established. This is hard to do – perhaps less so for Gen Z since this is the only world they know – but the chatbot needs the buyer’s personal information to engage intelligently. The buyer will only do that if the trade provides them with a better user experience that makes for a better purchasing process. This give-and-take dynamic is crucial for chatbots to have lasting value, and we’re definitely not there yet.
To some extent, this is less of an issue in the enterprise where internal chatbots are serving a closed, known community. Aside from the contact center – that’s an entirely different use case – chatbots can have many internal applications, such as with HR for onboarding new hires or providing ongoing training. They can be used by sales teams to help gather information/intelligence about customers or prospects, or by any team seeking specific expertise within the organization when working on a project.
In these cases, trust isn’t really the issue – unless there’s a Big Brother culture – and that frees up chatbots to do their best work. The easier it is for AI to build up a knowledge base from accessible sources, the more effective chatbots will be in automating processes. With messaging firmly embedded in a UC platform, the more valuable UC will become.
Thinking about buyers and sellers for the enterprise scenario, it’s best to view chatbots and AI as an LOB – line of business – decision, where there is a well-defined set of needs, such as HR training. The more precise the application, the more effective chatbots can be, provided there is an open dialog with workers for AI to learn from. Much of the conference focused on “conversational interfaces” or “conversational UI”, and this is where the developers really need to focus. In theory, chatbots can bring great value to the enterprise, but this isn’t about selling lipstick or dog food.
Enterprise chatbots will have to engage with workers in very different ways – they’re not customers, and they’re not looking for a social experience. For example, consider the issue of engaging with employees from across the spectrum of jobs – a one-size-fits-all approach as with consumers won’t work here. Executives won’t engage if your tone is too casual, while lower rank workers may be intimidated if your tone is too formal.
One of the big takeaways from Monage was the importance of nuance in how we communicate, and that brings us to UC. The value-add for UC comes from providing more choice for AI in the channels used to engage with employees and allow bots to do their work in gathering information for the task at hand.
This may sound a bit abstract, but a new world is opening up here. The learning curve is steep, but when chatbots can be intelligently used in the enterprise, UC will have a key role to play. We heard bits and pieces about this at Monage from familiar names like Avaya, Slack, SAP Mobile, RingCentral, Google, IBM, Twilio and Facebook, so this isn’t just me talking. For now, I would say stay tuned, and keep my mantra in mind about messaging being the new voice – there’s lots more to come.